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Individual patient data meta-analysis for the clinical assessment of coronary computed tomography angiography: protocol of the Collaborative Meta-Analysis of Cardiac CT (CoMe-CCT).

Oct 28, 2014 10/14

by Schuetz, Georg M; Schlattmann, Peter; Achenbach, Stephan; Budoff, Matthew; Garcia, Mario J; Roehle, Robert; Pontone, Gianluca; Meijboom, Willem Bob; Andreini, Daniele; Alkadhi, Hatem; Honoris, Lily; Bettencourt, Nuno; Hausleiter, Jorg; Leschka, Sebastian; Gerber, Bernhard L; Meijs, Matthijs FL; Shabestari, Abbas Arjmand; Sato, Akira; Zimmermann, Elke; Schoepf, Uwe J; Diederichsen, Axel; Halon, David A; Mendoza-Rodriguez, Vladimir; Hamdan, Ashraf; N?rgaard, Bjarne L; Brodoefel, Harald; ?vrehus, Kristian A; Jenkins, Shona MM; Halvorsen, Bj?rn A; Rixe, Johannes; Sheikh, Mehraj; Langer, Christoph; Martuscelli, Eugenio; Romagnoli, Andrea; Scholte, Arthur JHA; Marcus, Roy P; Ulimoen, Geir R; Nieman, Koen; Mickley, Hans; Nikolaou, Konstantin; Tardif, Jean-Claude; Johnson, Thorsten RC; Muraglia, Simone; Chow, Benjamin JW; Maintz, David; Laule, Michael; Dewey, Marc

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This article is from Systematic Reviews , volume 2 . Abstract Background: Coronary computed tomography angiography has become the foremost noninvasive imaging modality of the coronary arteries and is used as an alternative to the reference standard, conventional coronary angiography, for direct visualization and detection of coronary artery stenoses in patients with suspected coronary artery disease. Nevertheless, there is considerable debate regarding the optimal target population to maximize...
Source: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3576350

PubMed Central

71 71

Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts.

Oct 28, 2014 10/14

by Genders, Tessa S S; Steyerberg, Ewout W; Hunink, M G Myriam; Nieman, Koen; Galema, Tjebbe W; Mollet, Nico R; de Feyter, Pim J; Krestin, Gabriel P; Alkadhi, Hatem; Leschka, Sebastian; Desbiolles, Lotus; Meijs, Matthijs F L; Cramer, Maarten J; Knuuti, Juhani; Kajander, Sami; Bogaert, Jan; Goetschalckx, Kaatje; Cademartiri, Filippo; Maffei, Erica; Martini, Chiara; Seitun, Sara; Aldrovandi, Annachiara; Wildermuth, Simon; Stinn, Bjorn; Fornaro, Jurgen; Feuchtner, Gudrun; De Zordo, Tobias; Auer, Thomas; Plank, Fabian; Friedrich, Guy; Pugliese, Francesca; Petersen, Steffen E; Davies, L Ceri; Schoepf, U Joseph; Rowe, Garrett W; van Mieghem, Carlos A G; van Driessche, Luc; Sinitsyn, Valentin; Gopalan, Deepa; Nikolaou, Konstantin; Bamberg, Fabian; Cury, Ricardo C; Battle, Juan; Maurovich-Horvat, Pal; Bartykowszki, Andrea; Merkely, Bela; Becker, David; Hadamitzky, Martin; Hausleiter, Jorg; Dewey, Marc; Zimmermann, Elke; Laule, Michael

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This article is from BMJ : British Medical Journal , volume 344 . Abstract Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations.Design Retrospective pooled analysis of individual patient data.Setting 18 hospitals in Europe and the United States.Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary...
Source: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3374026

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